پديد آورنده :
فلاح زاده، عماد
عنوان :
پيش بيني نرخ ارز، با استفاده از يك سيستم فازي- عصبي نوع دوم مبتني بر خوشه بندي c-means فازي نوع دوم بازه اي
مقطع تحصيلي :
كارشناسي ارشد
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده برق و كامپيوتر
صفحه شمار :
نه،93ص.: مصور،جدول،نمودار
يادداشت :
ص.ع.به فارسي و انگليسي
استاد راهنما :
محمدعلي منتظري
تاريخ نمايه سازي :
30/7/92
استاد داور :
محمدرضا احمدزاده، مهران صفاياني
دانشكده :
مهندسي برق و كامپيوتر
چكيده فارسي :
به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي
چكيده انگليسي :
Forecasting Foreign Exchange Rates Using an IT2 FCM based Type 2 Neuro Fuzzy System Emad Fallahzadeh e fallahzadeh@ec iut ac ir Date of Submission January 2013 Dept of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran Degree M Sc Language Farsi Supervisor Mohammad Ali Montazeri montazeri@cc iut ac ir Abstract Predicting exchange rate is always an interesting issue for both economic and academic communities The power of forecasting exchange rate accurately could provide considerable benefits to both firms and investors But fluctuations in exchange rate which is caused by various parameters effective in market have made this job very complex and risky Until now various methods from economic techniques to pattern recognition techniques in past data have been used in this area of research One of the methods which has been very popular in last two decades is soft computing In this research a hybrid neuro fuzzy system based on interval type 2 fuzzy c means clustering MLP neural network and interval type 2 fuzzy model is proposed for predicting the noisy forex market To gain faster convergence in learning procedure combination of back resilient and back propagation is used Two EURUSD and USDCHF exchange rates from forex market are used for experiments The model is tested for convergence speed and accuracy of prediction It is also compared with its fuzzy c means based type 1 equivalent and a FLANN based neuro fuzzy system The performance of proposed model in convergence speed and prediction accuracy is proved by experimental results Keywords Exchange rate prediction Neuro fuzzy system IT2 fuzzy IT2 fuzzy c meansPDF created with pdfFactory trial version www pdffactory com
استاد راهنما :
محمدعلي منتظري
استاد داور :
محمدرضا احمدزاده، مهران صفاياني
